AL
AI21 Labs
Language model · Israel ·Mar 2025

Jamba 1.6 Large

Language Open (Restricted)
398B
Parameters

About Jamba 1.6 Large

Jamba 1.6 Large is an AI model developed by AI21 Labs, in the language category, released in 2025, made available as an open-weights model with 398B params.

On this page you'll find Jamba 1.6 Large's full specifications. Review provider pricing and benchmark scores below, or compare Jamba 1.6 Large head-to-head with other language models.

→ More models by AI21 Labs → All language models → AI benchmarks leaderboard

Links

Announcement ↗ Hugging Face ↗

Run Jamba 1.6 Large locally — what it takes

Jamba 1.6 Large (398B) is too large to run on a single consumer or Apple machine. At Q4 its weights alone are about 223 GB — it needs a multi-GPU / datacenter setup:

  • ≈ 1× AMD Instinct MI325X
  • ≈ 2× NVIDIA B200

Lower quantization (Q3/Q2) or CPU + system-RAM offload (e.g. ktransformers) reduces the requirement at the cost of speed.

Software support

·ExLlamaV2 ·KoboldCpp ·LM Studio ·MLX ·Ollama ·SGLang ·TensorRT-LLM ·llama.cpp ·vLLM ?KTransformers ?text-generation-webui

✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.

Datacenter GPU
20.7 tok/s
1 option →

Community

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Frequently asked questions

What is Jamba 1.6 Large? ▶

Jamba 1.6 Large is an AI model developed by AI21 Labs, in the language category, released in 2025. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created Jamba 1.6 Large? ▶

Jamba 1.6 Large was developed by AI21 Labs and released in 2025.

Is Jamba 1.6 Large open source or proprietary? ▶

Jamba 1.6 Large ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.

How much does Jamba 1.6 Large cost? ▶

Pricing for Jamba 1.6 Large depends on the provider. See the providers table on this page for the latest API rates.

How does Jamba 1.6 Large perform on benchmarks? ▶

Benchmark scores for Jamba 1.6 Large are listed on this page as they are published. You can compare it head-to-head with other models on the GenAIList compare tool.

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